Secure document management using blockchain

ABSTRACT

Disclosed is a secure document management system, for example, for documents pertaining to drug discovery. A document and its metainformation are obtained, and value features are extracted from the document based on identification of concepts associated with the document. An importance score of the document is determined based on the value features and the metainformation. A summarized view of the document is constructed based on the value features, the metainformation, the concepts and the importance score. A unique identifier is generated for the document and associated with the summarized view and the concepts of the document. A search query is processed, and the summarized view of the document is retrieved and displayed based on the query. A request for accessing the document is validated, and document access is allowed when the request is validated successfully. The document management may, for example, be facilitated using a blockchain platform.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a non-provisional patent application based upon a provisional patent application No. 62/664,432 as filed on Apr. 30, 2018, and claims priority under 35 U.S.C. 199(e).

TECHNICAL FIELD

The present disclosure relates generally to processing documents pertaining to a research field; and more specifically, to systems for securely managing documents, for example, documents pertaining to drug discovery. Moreover, the present disclosure relates to methods of managing documents in a secure manner.

BACKGROUND

In recent times, ability to share and retrieve information easily and timely has proved to be of great importance for research, business, innovation and any other field that requires an updated information for progressive functioning thereof. Consequently, multiple mechanisms and platforms were developed for sharing information such as discussions, books, journals, research findings and the like. However, the presently available platforms provide information that are already published (namely, disclosed) and/or made public by authors thereof.

Conventionally, online journals (like Elsevier) provide access to published documents on a subscription-basis. The pricing of these subscriptions is independent of the value of individual documents. However, such journals only deal with the published documents, and do not deal with unpublished information. In an example, if a research organization is interested in sharing its unpublished experimental findings with others, there is no mechanism for a fair valuation and sharing of a document that includes details of the experimental findings.

In other words, the presently available platforms are unable to provide unpublished information such as discussions, books, journals, research findings and the like. In an example, such information may belong to a first entity (such as an individual, an organization or a research institution) and may be associated with research findings from a clinical trial of a medicine for treating lung cancer. A second entity may not be able to access such research findings of the first entity until the clinical trial associated therewith gets published. Hence, the second entity may remain unaware of the research findings of the first entity. Consequently, entities end up working in silos, at times re-doing the same experiment, which has already been performed. This leads to longer drug development cycles, as the organizations (such as pharmaceutical companies) end up re-inventing the wheel. In another example, the first entity may be willing to share the experimental findings with the second entity. However, the sharing of the research findings may not be secured and the research findings may be misused. Furthermore, the first entity may not be able to control the use of information provided thereby.

Therefore, in light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks associated with sharing and retrieval of unpublished information.

SUMMARY

The present disclosure seeks to provide a secure document management system. The present disclosure also seeks to provide a method of managing documents in a secure manner. The present disclosure seeks to provide a solution to the existing problem of undependable and insecure platforms for management of documents. An aim of the present disclosure is to provide a solution that overcomes at least partially the problems encountered in prior art, and provides a reliable and secure platform for management of the document to prevent risks associated therewith.

In one aspect, an embodiment of the present disclosure provides a secure document management system, the system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device, wherein the server arrangement is configured to:

-   -   trigger an extraction module to obtain, from the first client         device, a document and metainformation pertaining to the         document;     -   process the document via the extraction module, wherein the         extraction module is configured to extract one or more value         features from the document based on an identification of one or         more concepts of the document that are identified as associated         with concepts stored in an ontological databank, the ontological         databank being communicably coupled with the extraction module;     -   determine, using a scoring module of the server arrangement, an         importance score of the document, wherein the scoring module is         configured to determine the importance score based on the one or         more value features and the metainformation pertaining to the         document;     -   construct a summarized view of the document based on the one or         more value features, the metainformation, the one or more         concepts and the importance score;     -   initialize a persistence module of the server arrangement to         generate a unique identifier for the document and associate the         unique identifier with the summarized view and with the one or         more concepts of the document;     -   receive, from the second client device, a search query and         process the search query to identify at least one concept         pertaining to the search query;     -   retrieve the summarized view of the document based on the unique         identifier of the document, when the at least one concept         pertaining to the search query matches at least one of the one         or more concepts of the document;     -   display, on a user interface of the second client device, the         summarized view of the document; and     -   validate a request, received from the second client device for         accessing the document, using a validation module of the server         arrangement, wherein the validation module is configured to         cause the first client device to allow the second client device         to access the document, when the request is validated         successfully.

In another aspect, an embodiment of the present disclosure provides a method of managing documents in a secure manner, wherein the method is implemented via a system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device, the method comprising:

-   -   triggering an extraction module to obtain, from the first client         device, a document and metainformation pertaining to the         document;     -   processing the document via the extraction module, to extract         one or more value features from the document based on an         identification of one or more concepts of the document that are         identified as associated with concepts stored in an ontological         databank, the ontological databank being communicably coupled         with the extraction module;     -   determining, using a scoring module of the server arrangement,         an importance score of the document based on the one or more         value features and the metainformation pertaining to the         document;     -   constructing a summarized view of the document based on the one         or more value features, the metainformation, the one or more         concepts and the importance score;     -   initializing a persistence module of the server arrangement to         generate a unique identifier for the document and associate the         unique identifier with the summarized view and with the one or         more concepts of the document;     -   receiving, from the second client device, a search query and         processing the search query to identify at least one concept         pertaining to the search query;     -   retrieving the summarized view of the document based on the         unique identifier of the document, when the at least one concept         pertaining to the search query matches at least one of the one         or more concepts of the document;     -   displaying, on a user interface of the second client device, the         summarized view of the document; and     -   validating a request, received from the second client device for         accessing the document, using a validation module of the server         arrangement, wherein the validation module is configured to         cause the first client device to allow the second client device         to access the document, when the request is validated         successfully.

Embodiments of the present disclosure substantially eliminate or at least partially address the aforementioned problems in the prior art, and enables a user to securely manage the document by preventing associated risks therewith.

Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments construed in conjunction with the appended claims that follow.

It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:

FIGS. 1 and 2 schematic illustrations of network environments, wherein a secure document management system for executing a document access transaction is implemented, pursuant to different embodiment of the present disclosure;

FIG. 3 is a schematic illustration of a high-level architecture of a network environment in which a system for executing a document access transaction is implemented, pursuant to a specific embodiment of the present disclosure;

FIGS. 4A and 4B collectively are a flow chart depicting steps of a method for managing documents in a secure manner, in accordance with an embodiment of the present disclosure;

FIGS. 5A and 5B are example views of a graphical user interface that are presented to a first user of a first client device, in accordance with an embodiment of the present disclosure; and

FIGS. 6A and 6B are example views of a graphical user interface that are presented to a second user of a second client device, in accordance with an embodiment of the present disclosure.

In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.

DETAILED DESCRIPTION OF EMBODIMENTS

The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practicing the present disclosure are also possible.

In one aspect, an embodiment of the present disclosure provides a secure document management system, the system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device, wherein the server arrangement is configured to:

-   -   trigger an extraction module to obtain, from the first client         device, a document and metainformation pertaining to the         document;     -   process the document via the extraction module, wherein the         extraction module is configured to extract one or more value         features from the document based on an identification of one or         more concepts of the document that are identified as associated         with concepts stored in an ontological databank, the ontological         databank being communicably coupled with the extraction module;     -   determine, using a scoring module of the server arrangement, an         importance score of the document, wherein the scoring module is         configured to determine the importance score based on the one or         more value features and the metainformation pertaining to the         document;     -   construct a summarized view of the document based on the one or         more value features, the metainformation, the one or more         concepts and the importance score;     -   initialize a persistence module of the server arrangement to         generate a unique identifier for the document and associate the         unique identifier with the summarized view and with the one or         more concepts of the document;     -   receive, from the second client device, a search query and         process the search query to identify at least one concept         pertaining to the search query;     -   retrieve the summarized view of the document based on the unique         identifier of the document, when the at least one concept         pertaining to the search query matches at least one of the one         or more concepts of the document;     -   display, on a user interface of the second client device, the         summarized view of the document; and     -   validate a request, received from the second client device for         accessing the document, using a validation module of the server         arrangement, wherein the validation module is configured to         cause the first client device to allow the second client device         to access the document, when the request is validated         successfully.

In another aspect, an embodiment of the present disclosure provides a method of managing documents in a secure manner, wherein the method is implemented via a system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device, the method comprising:

-   -   triggering an extraction module to obtain, from the first client         device, a document and metainformation pertaining to the         document;     -   processing the document, via the extraction module, to extract         one or more value features from the document based on an         identification of one or more concepts of the document that are         identified as associated with concepts stored in an ontological         databank, the ontological databank being communicably coupled         with the extraction module;     -   determining, using a scoring module of the server arrangement,         an importance score of the document based on the one or more         value features and the metainformation pertaining to the         document;     -   constructing a summarized view of the document based on the one         or more value features, the metainformation, the one or more         concepts and the importance score;     -   initializing a persistence module of the server arrangement to         generate a unique identifier for the document and associate the         unique identifier with the summarized view and with the one or         more concepts of the document;     -   receiving, from the second client device, a search query and         processing the search query to identify at least one concept         pertaining to the search query;     -   retrieving the summarized view of the document based on the         unique identifier of the document, when the at least one concept         pertaining to the search query matches at least one of the one         or more concepts of the document;     -   displaying, on a user interface of the second client device, the         summarized view of the document; and     -   validating a request, received from the second client device for         accessing the document, using a validation module of the server         arrangement, wherein the validation module is configured to         cause the first client device to allow the second client device         to access the document, when the request is validated         successfully.

The secure document management system and the method of managing documents in a secure manner as described in the present disclosure provides a single platform for secure management of a document. Typically, the secure document management system provides a platform for secured exchange of a published or an unpublished document for various commercial actions such as sale, lease, licensing, rent and so forth. Essentially, the server arrangement of the aforesaid secure document management system discloses a brief information associated with the document. Subsequently, the aforesaid system prevents the document from various security threats such as theft, cyber-attacks, plagiarism and so forth. Moreover, the server arrangement reduces human intervention for valuating the document. Consequently, the server arrangement prevents any unfairness or biasness in the process of valuation of the document. Beneficially, the server arrangement further provides the user of the second client device (namely, consumer) with a plurality of available options and brief information (such as, the summarized view, the metainformation, and so forth) associated with the document, related to the technical field of the search query provided by the user of the second client device. Consequently, the server arrangement enables the user of the second client device to make an informed decision while choosing a document for a commercial action. Moreover, the aforesaid server arrangement is configured to present (namely, display) only the summarized view of the document, namely brief information associated with the document, before a rightful access to the document is provided to an authorized party. In other words, the access to the document (for example, a document containing highly sensitive and confidential information) is not provided, unless the request from the second client device is validated successfully.

It will be appreciated that the aforesaid secure document management system and the aforesaid method are not limited to facilitating the secure document management for only a single document. The system and method can be employed to facilitate secure document management for multiple documents. The multiple documents could comprise documents owned by a same first client device or documents owned by different first client devices. In such a case, the aforesaid steps are implemented for each document of the multiple documents.

Optionally, the aforementioned document is related to a current research work performed in a research organization. Throughout the present disclosure, the term “document” refers to a set of files in which an observation made in a scientific investigation or experiment is recorded, wherein the observation can be recorded in a form of one or more types of data. Some examples of various types of data are text data, tabular data, image data, video data and audio data. Thus, files can be in any suitable file formats depending upon the type of data that is stored therein. As an example, the set of files could comprise a single file having one or more of: a written text, one or more tables, one or more graphs, or a set of images. As another example, the set of files could comprise a plurality of files having different types of data, for example, such as a written text, one or more tables, one or more graphs, a set of images, one or more videos, or one or more audio clips.

Throughout the present disclosure, the term “server arrangement” refers to an arrangement of one or more servers that includes one or more processors configured to perform various operations, for example, as mentioned earlier. Optionally, the server arrangement includes any arrangement of physical or virtual computational entities capable of performing the various operations. The term “one or more processors” may refer to one or more individual processors, processing devices and various elements associated with a processing device that may be shared by other processing devices. Additionally, the one or more individual processors, processing devices and elements are arranged in various architectures for responding to and processing the instructions that drive the aforesaid system.

Moreover, it will be appreciated that the server arrangement can be implemented by way of a single hardware server. The server arrangement can alternatively be implemented by way of a plurality of hardware servers operating in a parallel or distributed architecture. As an example, the server arrangement may include components such as memory, a processor, a network adapter and the like, to store and process information pertaining to the document and to communicate the processed information to other computing components, for example, such as a client device.

Throughout the present disclosure, the term “server” generally refers to a device executing an application, program, or process in a client/server relationship that responds to requests for information or services by another application, program, process or device (namely, a client) on a data communication network. Optionally, a given server is implemented by way of a device executing a computer program that provides various services (for example, such as a database service) to other devices, modules or apparatus.

The term “client device” generally refers to a device executing an application, program, or process in a client/server relationship that requests information or services from another application, program, process or device (namely, a server) on a data communication network. Importantly, the terms “client” and “server” are relative, as an application may be a client to one application but a server to another application.

Notably, the first and second client devices are configured to function as a “client” in a client/server relationship with the server arrangement. However, the first and second client devices may be configured to function as a “server” in a client/server relationship with other computing devices. Throughout the present disclosure, the terms “first client device” and “second client device” refer to devices associated with a first user and a second user that acts as clients to the server arrangement in a client/server relationship, wherein such devices can be personal devices or servers in local environments of the first user and the second user, respectively. As an example, the first client device can be an internal server of the research organization where the current research work has been performed (namely, from where the document has originated), while the second client device can be an internal server of another research organization that is interested in accessing the document.

It will be appreciated that the document may have been authored or co-authored by one or more authors. The first user can be any one of the one or more authors, a representative of the one or more authors, or an owner of the document, who uses the first client device to perform commercial transactions of the document (for example, such as sale, licensing and so forth). On the other hand, the second user can be, for example, an individual or a representative of a group of individuals or an organization seeking access to the document, wherein the second user uses the second client device to perform commercial actions (for example, such as purchase, lease, rent, and so forth) for consuming the document.

Throughout the present disclosure, the term “extraction module” refers to a module comprising programmable components. Optionally, the extraction module is implemented by way of a trusted software application that, when executed at the first client device, obtains the document and the metainformation pertaining to the document. Optionally, in such a case, the trusted software application is received (for example, downloaded) from the server arrangement or a trusted third party. The trusted third party can be a publicly-accessible digital distribution platform, for example, such as Google Play®, the App Store® (for iOS®) and the like. Moreover, the extraction module is implemented by way of a web platform that, when executed at the server arrangement, obtains the document and the metainformation pertaining to the document.

Optionally, the extraction module is implemented either on the server arrangement or on the first client device, based on a preference of a user of the first client device. Typically, the user of the first client device provides a preference for the environment to be utilized, for the implementation of the extraction module. In other words, the user of the first client device may enable the implementation of the extraction module on an environment provided by the server arrangement or the first client device. In an embodiment, the document and the metainformation is provided to the server arrangement implementing the extraction module. In another embodiment, the user of the first client device may select the environment provided by the first client device for the implementation of the extraction module. In such a case, the extraction module implemented in the first client device is configured to process the document to extract the one or more value features from the document. Furthermore, the one or more value features from the document extracted by the first client device along with the metainformation are provided to the server arrangement.

Pursuant to embodiments of the present disclosure, when triggered, the extraction module is configured to present a graphical user interface to the first user that allows the first user to submit to the extraction module the document and the metainformation pertaining to the document. Optionally, the metainformation pertaining to the document is submitted in a form of a meta file.

Optionally, in order to submit the metainformation, the extraction module is configured to provide the first user with a form having input fields, via the graphical user interface. The first user is required to fill the form to provide the metainformation pertaining to the document. Optionally, the extraction module is configured to collate the metainformation pertaining to the document into the meta file.

Optionally, the metainformation pertaining to the document comprises information about one or more of: names of the one or more authors, name of a research organization where the current research work has been performed, a statistical significance of the current research work, a set of keywords associated with the current research work, one or more research fields to which the current research work pertains, a hypothesis of the current research work, an experiment performed during the current research work, a stage of drug development to which the current research work is applicable. Additionally, optionally, the metainformation also comprises information pertaining to cost incurred in the current research work of the one or more authors.

Optionally, the extraction module is configured to allow, via the graphical user interface, the first user to view and edit the metainformation previously submitted by the first user.

Moreover, optionally, the server arrangement is configured to provide the first user, via a graphical user interface of the first client device, with a Single Sign-On (SSO) feature, based on stored credentials of the first user. Optionally, the graphical user interface of the first client device allows the first user to input his/her credentials (for example, a user identification and a password) to complete a sign-in procedure. Additionally, optionally, the graphical user interface of the first client device allows the first user to store such credentials on the first client device, thereby allowing the first user to sign-in without a need to input the credentials.

Beneficially, the server arrangement is configured to authenticate the first user prior to allowing the first user to submit the document. This potentially prevents an unauthorized party from masquerading as the first user.

Optionally, when signing-up for the first time, the first user is required to provide one-time information, for example, including information about the one or more authors. Optionally, the information about the one or more authors is indicative of at least one of: names or unique identifiers of the one or more authors, academic qualifications of the one or more authors, academic institutes from where the one or more authors obtained the academic qualifications, research organizations and/or departments to which the one or more authors are currently affiliated, areas of expertise of the one or more authors, areas of interest of the one or more authors, digital libraries where the one or more authors have made publications.

Optionally, the extraction module is configured to communicate the information about the one or more authors to the server arrangement, wherein the information about the one or more authors is to be utilized by the scoring module of the server arrangement. More optionally, the information about the one or more authors is communicated to the server arrangement during an initial sign-up procedure.

Furthermore, optionally, the extraction module is configured to convert a data format of the document into a predefined data format prior to extracting the one or more value features from the document. Optionally, the predefined data format is a file format, for example, such as a JavaScript Object Notation (JSON) format. It will be appreciated that the document obtained from the first client device can be in any file format, for example, such as a Portable Document Format (PDF), Joint Photographic Experts Group (JPEG) format, Microsoft Word document format, Microsoft Excel worksheet format and so forth.

Pursuant to embodiments of the present disclosure, the extraction module is configured to process the document to extract the one or more value features therefrom. Optionally, when processing the document, different sections of the document are identified and at least one of the sections of the document is further processed to extract the one or more value features, wherein the one or more value features are indicative of entities and semantic inter-relationships between the entities as mentioned in the at least one of the sections of the document.

Optionally, the document is related to a current research work of one or more authors, and wherein the one or more value features of the document comprise information elements indicative of entities and semantic inter-relationships between the entities. Beneficially, a semantic inter-relationship between two given entities is indicative of a causal relationship between the two given entities. As an example, in drug discovery, examples of a causal relationship between a drug and a disease could be “causes”, “inhibits”, “catalyzes” and so on.

Optionally, the extraction module is configured to compare words (and/or phrases) occurring in the at least one of the sections of the document with the concepts stored in the ontological databank, and to identify the one or more concepts of the document based on the comparison with the concepts stored in the ontological databank. Optionally, in this regard, the extraction module is configured to stem the words prior to performing said comparison, and identify words matching the concepts stored in the ontological databank as the one or more concepts of the document.

Optionally, sentences present in the at least one of the sections of the document are processed by employing a frame semantic parsing technique to generate semantic frames, wherein these semantic frames form a part of the one or more value features. Optionally, the frame semantic parsing technique employs a directed acyclic transition-based recurrent neural network.

In the frame semantic parsing technique, sentences or phrases in a natural language are parsed and processed to generate the semantic frames. In other words, lexical targets (namely, words and phrases) in their sentential contexts are processed to generate the semantic frames. Herein, the term “semantic frame” refers to a coherent structure of related concepts that specify features that are typically associated with a particular word (for example, attributes, functions and interactions of a particular entity). As an example, a semantic frame observed in research work related to drug discovery could include at least two of: a drug, a pathway, a target, a disease.

Such a frame semantic parsing technique is optionally implemented using known techniques and models, for example as described in a published paper, titled “SLING: A framework for frame semantic parsing” (Michael Ringgaard et. al., available here https://arxiv.org/abs/1710.07032).

Beneficially, the frame semantic parsing technique employs the aforementioned ontological databank. It will be appreciated that the frame semantic parsing technique identifies the entities and their semantic inter-relationships even when the entities and their semantic inter-relationships may be defined very subjectively in the document.

Throughout the present disclosure, the term “ontological databank” refers to a data repository that is configured to store information about a set of concepts related to a technical field (namely, a subject area, a technical domain and so forth), wherein said information is indicative of types of concepts, properties of the concepts and semantic inter-relationships between the concepts. Optionally, the ontological databank is configured to store the information about the set of concepts in a structured manner. Additionally, optionally, the ontological databank is configured to store information on how a certain concept in a certain technical field may be associated with one or more concepts in other field(s).

In an embodiment, the ontological databank is stored at the first client device. In another embodiment, the ontological databank is stored at a database arrangement associated with the server arrangement. Optionally, the database arrangement comprises one or more databases.

For illustration purposes only, there will now be considered an example document related to drug discovery, wherein an abstract of the document is as follows:

“This experiment was carried out in vivo to check if IL1b mRNA did not show any change in Cortex and Hippocampi. All LPS-induced changes were restored in 70 day old rats. 5 PUPs were treated with Saline and LPS (IP 2 mg/kg). mRNA level of pro-inflammatory cytokine (IL1b) was examined. Found that IL1b mRNA was left significantly unregulated in Substantia nigra. Further experiments like WB, ELISA were also conducted.”

In such a case, the abstract of the example document is processed, by employing an ontological databank related to drug discovery, to extract value features indicative of entities and their semantic inter-relationships, wherein the entities and their types can be identified as follows:

Drug: LPS

Disease: pro-inflammatory cytokine

Target: Cortex and Hippocampi

Moreover, the semantic inter-relationships can be represented as follows: LPS-no effect-Cytokine

Moreover, optionally, upon receiving the one or more value features and the metainformation pertaining to the document, the server arrangement is configured to process the one or more value features and the metainformation to check the authenticity of the document. This potentially prevents a fraudulent user or the first user from uploading a facsimile of the document intentionally or ignorantly, thereby preventing plagiarism and identity theft.

Pursuant to embodiments of the present disclosure, the scoring module of the server arrangement, in operation, determines the importance score of the document based on the one or more value features and the metainformation pertaining to the document and optionally, the aforementioned information about the one or more authors.

Optionally, the scoring module is configured to access, based upon the information about the one or more authors, information indicative of entities and semantic inter-relationships specific to a previous research work of the one or more authors. Optionally, in this regard, the scoring module is configured to:

-   -   obtain, from a plurality of database servers, other documents         authored by at least one of the one or more authors;     -   process the other documents to identify the entities and the         semantic inter-relationships specific to the previous research         work; and     -   store the information indicative of the entities and the         semantic inter-relationships specific to the previous research         work.

Hereinabove, the term “database servers” refers to database servers related to a plurality of digital libraries that publish technical documents authored by various authors or research organizations, while the term “other documents” refers to all the documents authored or co-authored previously (namely, prior to the current research work) by the at least one of the one or more authors that are available in the public domain, and therefore, represent the previous research work of the one or more authors. Such published technical documents may, for example, be pre-clinical reports, clinical reports, scientific articles, theses, granted patents, published patent applications and so on.

Optionally, in order to obtain the other documents, the plurality of database servers are queried using the names or other unique identifiers of the one or more authors (as obtained from the information about the one or more authors).

Optionally, when processing a given other document, different sections of the given other document are identified and at least one of the different sections of the given other document is further processed to identify the entities and the semantic inter-relationships specific to the previous research work. It will be appreciated that technical documents typically have well-defined sections that can be identified from their respective headings, and therefore, it is possible to select at least one of these sections for further processing. As an example, a scientific report related to an experiment may include various sections having suitable headings, for example, such as ‘Abstract’, ‘Introduction’, ‘Materials and Methods’, ‘Results’, ‘Discussion’, ‘Conclusion’ and ‘References’. In such a case, the section(s) ‘Abstract’ and/or ‘Conclusion’ may be further processed to identify entities and semantic inter-relationships mentioned in the scientific report. As another example, a patent document typically includes sections having headings, for example, such as ‘Abstract’, ‘Background’, ‘Summary’, ‘Brief Description of Drawings’, ‘Detailed Description’ and ‘Claims’. In such a case, the section(s) ‘Abstract’ and/or ‘Claims’ may be further processed to identify entities and semantic inter-relationships mentioned in the patent document.

Optionally, the other documents are processed by employing the aforementioned frame semantic parsing technique to generate corresponding semantic frames. Optionally, in such a case, sentences present in at least one section of each of the other documents are parsed and processed to generate the semantic frames. Optionally, these semantic frames form a part of the information indicative of the entities and the semantic inter-relationships specific to the previous research work.

Optionally, the information indicative of the entities and the semantic inter-relationships specific to the previous research work is stored at a data repository of the server arrangement. Optionally, the data repository is implemented by way of data memory associated with at least one of the one or more processors of the server arrangement. Alternatively, optionally, the data repository is implemented by way of the database arrangement associated with the server arrangement.

Optionally, the scoring module is configured to obtain and process the other documents even before the document is obtained by the extraction module. It will be appreciated that the other documents can be obtained and processed after the initial sign-up procedure.

Moreover, optionally, the scoring module is configured to process the one or more value features and/or the metainformation pertaining to the document to determine a technical field of the current research work. Optionally, the scoring module is configured to access, based upon the technical field of the current research work, information indicative of entities and semantic inter-relationships related to the technical field. Optionally, in this regard, the scoring module is configured to:

-   -   obtain, from the plurality of database servers, a plurality of         documents pertaining to the technical field of the current         research work;     -   process the plurality of documents to identify the entities and         the semantic inter-relationships related to the technical field;         and     -   store the information indicative of the entities and the         semantic inter-relationships related to the technical field.

Optionally, in order to obtain the plurality of documents pertaining to the technical field of the current research work, the plurality of database servers are queried using key words (namely, key strings) that are relevant to the technical field. Hereinabove, the term “database servers” refers to the database servers related to the plurality of digital libraries that publish technical documents authored by various researchers or research organizations, while the term “plurality of documents” refers to all the documents pertaining to the technical field that are available in the public domain, and therefore, represent knowledge available publicly.

Optionally, when processing a given document, different sections of the given document are identified and at least one of the different sections of the given document is further processed to identify the entities and the semantic inter-relationships related to the technical field, as described earlier.

Optionally, the information indicative of the entities and the semantic inter-relationships related to the technical field is stored at the aforementioned data repository or another data repository of the server arrangement.

Optionally, the scoring module is configured to obtain and process the plurality of documents even before the aforementioned document is obtained by the extraction module. Optionally, the plurality of documents are obtained and processed for a plurality of technical fields; for each technical field, information indicative of entities and semantic inter-relationships related to that technical field is stored at the data repository and updated from time to time.

Optionally, the scoring module is configured to:

-   -   compare the entities and the semantic inter-relationships         specific to the current research work with the entities and the         semantic inter-relationships related to the technical field of         the current research work;     -   compare the entities and the semantic inter-relationships         specific to the current research work with the entities and the         semantic inter-relationships specific to the previous research         work of one or more authors; and     -   determine the importance score based upon said comparisons.

Optionally, in this regard, the scoring module is configured to:

-   -   generate a current-work graph representing the entities and the         semantic inter-relationships specific to the current research         work;     -   generate a knowledge graph representing the entities and the         semantic inter-relationships related to the technical field of         the current research work;     -   generate a previous-work graph representing the entities and the         semantic inter-relationships specific to the previous research         work; and     -   perform the aforementioned comparisons using the current-work         graph, the previous-work graph and the knowledge graph.

Optionally, the knowledge graph represents the entities and the semantic inter-relationships related to the technical field, and weights assigned to the semantic inter-relationships. Likewise, optionally, the previous-work graph represents the entities and the semantic inter-relationships specific to the previous research work, and weights assigned to the semantic inter-relationships. Similarly, optionally, the current-work graph represents the entities and the semantic inter-relationships specific to the current research work, and weights assigned to the semantic inter-relationships.

Optionally, in this regard, a given graph is generated by linking the entities according to the semantic inter-relationships between them. In the given graph, the entities are represented by nodes of the given graph, while the semantic inter-relationships between the entities are represented by edges (namely, links) between the nodes.

As mentioned above, the semantic inter-relationships between the entities have weights assigned thereto. Optionally, in case of the previous-work graph, a given semantic inter-relationship between two entities is assigned a weight based upon at least one of: a type of causal relationship represented by the given semantic inter-relationship between the two entities, the number of documents authored by the at least one of the one or more authors in which the given semantic inter-relationship occurred, ranks of digital libraries where the documents were published.

Likewise, optionally, in case of the knowledge graph, a given semantic inter-relationship between two entities is assigned a weight based upon at least one of: a type of causal relationship represented by the semantic inter-relationship between the two entities, the number of documents in which the semantic inter-relationship occurred, ranks of digital libraries where the documents were published.

Moreover, optionally, in case of the current-work graph, a given semantic inter-relationship between two entities is assigned a weight based upon the weight of the given semantic inter-relationship in the knowledge graph.

It will be appreciated that the weight of the given semantic inter-relationship represents a strength of the given semantic inter-relationship.

Furthermore, optionally, the scoring module is configured to:

-   -   process the information about the one or more authors, whilst         taking into consideration rankings of the academic institutes,         the research organizations and the digital libraries, to         determine a reputation factor associated with the document; and     -   determine the importance score of the document, based upon the         reputation factor.

Moreover, optionally, the scoring module is configured to:

-   -   process the information pertaining to the cost incurred in the         current research work to determine a cost factor associated with         the document; and     -   determine the importance score of the document, based upon the         cost factor.

Furthermore, optionally, the scoring module is configured to:

-   -   process the information about the statistical significance of         the current research work, whilst taking into account a rank of         the research organization where the current research work has         been performed, to determine a statistical-significance factor         associated with the document; and     -   determine the importance score of the document, based upon the         statistical-significance factor.

Optionally, the extraction module is further configured to store the document on a temporary basis. In other words, the extraction module may store the document temporarily in a volatile data storage unit. Typically, the extraction module stores the document temporarily, in order to ensure extraction of the one or more value features from the document. Specifically, the volatile storage employed by the extraction module enables the author to prevent the storage of the document in any non-volatile information repository or database of the server arrangement. Consequently, sensitive documents (namely, confidential document) may be prevented from security threats. Moreover, the extraction module is configured to discard (namely, delete) the document after the processing of the document to extract the one or more value features form the document.

Throughout the present disclosure, the term “importance score” refers to a rating (namely, a grade or a value) that is determined for the document, wherein the importance score is indicative of a quantified importance of the current research work from a technical point of view. Thus, the importance score can be used to provide a potential consumer with an insight into the current research work, and to help the consumer in deciding whether or not to purchase the document. Moreover, the importance score can be used to provide the first user with a guidance for pricing the document for selling the document to research organizations or personnel that are interested in buying the document.

Moreover, optionally, the importance score is a monetary value. Optionally, the monetary value is in a crypto-currency for enabling future transactions of the document using a blockchain. It will be appreciated that the monetary value can alternatively be in any suitable currency, as required.

As mentioned earlier, the server arrangement is configured to construct the summarized view of the document based on at least one of: the one or more value features, the metainformation, the one or more concepts of the document and the importance score. Notably, the summarized view of the document provides a concise outline of the document representative of significant features of the document. Furthermore, the summarized view of the document provides the second user with a synoptic description of the document.

Optionally, the summarized view comprises a brief description of the document, bibliographical information pertaining to the document, a list of keywords associated with the document, and the importance score of the document. Optionally, the list of keywords associated with the document includes at least one of the one or more concepts of the document. Moreover, optionally, the server arrangement is configured to employ Natural Language Generation (NLG) techniques to generate the brief description of the document based on the one or more concepts of the document. Moreover, the bibliographical information pertaining to the document includes information relating to the one or more authors of the document, technical field of the document, a completion date of the document and so forth.

Optionally, the list of tags associated with the document comprises at least one of the one or more concepts associated with the document, wherein the at least one of the one or more concepts is selected based on a frequency of occurrence of the at least one of the one or more concepts in the document. Specifically, the frequency of occurrence of the one or more concepts in the document may vary based on the document. Furthermore, the frequency of occurrence of a given concept in the document is representative of relevance of the given concept for the document. Therefore, frequency of occurrence of each of the one or more concept is analyzed. Consequently, at least one of the one or more concepts having a frequency of occurrence over a predefined threshold is selected to be included in the list of tags. Furthermore, the predefined threshold for selection of document may be defined by the user of the first client device or by the server arrangement based on a plurality of parameters such as length of the document, mean frequency of occurrence of the one or more concepts of the document, median frequency of occurrence of the one or more concepts of the document, number of the one or more concepts of the document and so forth.

Furthermore, as mentioned earlier, the persistence module of the server arrangement is configured to generate a unique identifier for the document, and associate the unique identifier with the summarized view and with the one or more concepts of the document. Optionally, the unique identifier is a string of alphabets, numbers, symbols or a combination thereof. Specifically, the unique identifier serves as a means for identification and retrieval of the summarized view of the document (and consequently, the document).

Optionally, the persistence module is configured to store the unique identifier of the document with the summarized view and with the one or more concepts of the document in a non-volatile storage location, for example, such as at least one of the one or more databases of the database arrangement.

Optionally, the unique identifier of the document is stored with the one or more concepts of the document in a form of inverted indices. Optionally, the persistence module is configured to map a given concept to unique identifiers of a plurality of documents in which the given concept is identified. In other words, the given concept acts as an index to the unique identifiers of the plurality of documents in which the given concept is identified.

For illustration purposes only, there will now be considered an example scenario, wherein:

-   -   a first document has a unique identifier “B6A34” that is         associated with concepts, “Cancer”, “Lung Cancer”, “EGFR”         identified therefrom;     -   a second document has a unique identifier “C8X45” that is         associated with concepts “Cancer”, “Breast Cancer”, “Lung         Cancer” identified therefrom; and     -   a third document has a unique identifier “S3F89” that is         associated with concepts “Cancer”, “Diabetes” and “EGFR”         identifier therefrom.

In the illustrated example, a table below represents the mapping of the concepts to the unique identifiers as follows:

Concept Unique Identifier(s) Cancer B6A34, C8X45, S3F89 Lung Cancer B6A34, C8X45 Breast Cancer C8X45 EGFR B6A34, S3F89 Diabetes S3F89

It will be appreciated that such inverted indexing is particularly beneficial when there are a large number of documents (for example, in millions or more), because searching for documents matching a particular concept can be performed relatively fast.

Moreover, as mentioned earlier, the server arrangement is configured to receive the search query from the second client device and process the search query to identify the at least one concept pertaining to the search query. Specifically, the second client device is the device associated with the second user who is interested in accessing the document.

Optionally, the server arrangement is configured to present the graphical user interface to the second user that allows the second user to input the search query. As an example, the second user can provide the search query in an input field displayed on the graphical user interface of the second client device. The search query may, for example, comprise a set of keywords entered by the second based on his/her area of interest.

Optionally, the search query is parsed and compared with the concepts stored in the ontological databank to identify a possible match therebetween. Additionally, optionally, a spell check is performed on the search query.

Optionally, the search query comprises one or more query segments (namely, fragments, phrases and so forth) and contextual (namely, conceptual, semantic and so forth) associations therebetween. A query segment is a part of a search query that has a significant contextual meaning. As an example, the search query can be as follows: “drugs tablets for curing lung cancer”. In such a case, the query segments can be as follows: “drugs”, “tablets”, “curing”, “lung”, and “cancer”. Optionally, the one or more query segments are compared with the concepts stored in the ontological databank to identify the at least one concept pertaining to the search query.

Optionally, the server arrangement is configured to expand the search query to include at least one of: lexical variants for at least one of the one or more query segments, synonyms of at least one of the one or more query segments, abbreviations of at least one of the one or more query segments, word stems of at least one of the one or more query segments. Additionally, optionally, the lexical variants, the synonyms, the abbreviations and/or the word stems are processed into a canonical form (namely, to standardize the one or more query segments).

Moreover, optionally, the server arrangement is configured to convert the search query into a machine-readable format. Optionally, the search query is converted into the JSON format or any other suitable format.

Furthermore, as mentioned earlier, the server arrangement is configured to retrieve the summarized view of the document based on the unique identifier of the document, when the at least one concept pertaining to the search query matches at least one of the one or more concepts of the document. Optionally, in this regard, the at least one concept pertaining to the search query is compared with each of one or more concepts of multiple documents that were associated and stored by the persistence module.

Subsequently, for each concept that is found to match the at least one concept pertaining to the search query, summarized views of all documents whose unique identifiers are associated with that concept are retrieved. As mentioned previously, the unique identifiers of the documents are associated with the summarized views of the documents. Therefore, when the at least concept pertaining to the search query matches the at least one of the one or more concepts of the document, the summarized view of the document is retrieved.

Optionally, the server arrangement is configured to present, via the graphical user interface of the second client device, a list of documents that matched the search query.

Optionally, a recommendation module of the server arrangement is configured to display a list of summarized views of one or more documents whose unique identifiers are mapped to the at least one of the one or more concepts of the document. The recommendation module is implemented module of the server arrangement comprising programmable components. As aforementioned, a given concept is mapped to unique identifiers of a plurality of documents in which the given concept is identified. Therefore, at least one of the one or more concepts of the document comprises unique identifiers of one or more documents mapped therewith. Consequently, the summarized views of the one or more documents are displayed at the second client device using the recommendation module. Beneficially, a user of the second client device, accessing the document may be interested in the one or more documents whose unique identifiers are mapped to the at least one of the one or more concepts of the document.

Referring to Table 1, in an example, the one or more concepts of a given document with unique identifier “B6A34” may be “Cancer”, “Lung Cancer”, and “EGFR”. Specifically, the recommendation module is configured to display summarized views of one or more documents whose unique identifiers are mapped to at least one of the one or more concepts of the given document. More specifically, the recommendation module is configured to display summarized views of one or more documents whose unique identifiers are mapped to at least one of the one or more concepts: “Cancer”, “Lung Cancer”, and “EGFR”. Therefore, the summarized views of documents with unique identifiers “C8X45” and “S3F89” are displayed.

Moreover, the server arrangement is configured to display, on the graphical user interface of the second client device, the summarized view of the document. Optionally, in this regard, the summarized view is displayed to the second user, based upon a user's selection of the document from the list of documents. This allows the second user to check whether or not the document is relevant to his/her search query, thereby helping him/her make a decision regarding the document.

It will be appreciated that the summarized view can alternatively be constructed on the fly, when the summarized view is required to be displayed to the second user. In such cases, the summarized view is not pre-stored.

Pursuant to embodiments of the present disclosure, the graphical user interface allows the user to initiate the request for accessing the document. In this regard, the server arrangement is configured to validate the request, received from the second client device for accessing the document, using the validation module of the server arrangement.

Optionally, in this regard, the validation module is configured to validate an identity of the second user and/or a payment transaction made by the second user for accessing the document.

Optionally, upon successful validation, the first client device is configured to allow the second client device to access the document over a data communication network that is different from the one or more data communication networks. As mentioned earlier, the server arrangement is communicably coupled with the first client device and the second client device using the one or more data communication networks. Therefore, allowing the access of the document over the data communication network that is different from the one or more data communication networks ensures security of the document. In an instance, when a security of the one or more data communication networks is compromised, the security of the document may not be breached.

Moreover, it will be appreciated that the scoring module, the persistence module and the validation module can be implemented by way of a single processor or separate processors of the server arrangement.

Furthermore, optionally, a document sharing module is configured to encrypt the document using a key of the first client device. Optionally, the document sharing module is configured to generate the key to be used for encrypting the document. The document is encrypted to prevent unauthorized access of the document from malicious parties masquerading as the second client device. Optionally, an implementation of the document sharing module is partially divided between the first client device and the server arrangement. In other words, some operations of the document sharing module are optionally performed at the first client device, while other operations of the document sharing module are performed at the server arrangement.

Furthermore, the key that is used to encrypt the document may, for example, be a hash function, a mathematical operator, a mathematical operation and so forth.

Optionally, the document sharing module is configured to store the encrypted document in a distributed file system. The distributed file system provides a protocol for storing and exchanging documents for peer-to-peer transfers. Furthermore, the encrypted document is stored at various peer nodes pertaining to various public nodes of the distributed file system. The peer nodes are not dependent on each other; this ensures that the distributed file system has no failures due to non-functionality of any of the peer nodes. Once stored, the content of the encrypted document cannot be changed. This makes the distributed file system secure. An example of the distributed file system is InterPlanetary File System (IPFS).

Optionally, in this regard, the distributed file system is operable to generate a hash that uniquely identifies the document. Optionally, in order to generate the hash of the document, the distributed file system applies a hash operation on a combination of: the encrypted document, metadata of the document and a file format of the document. The hash of the document is a string of alphanumeric characters having a fixed length. It will be appreciated that the length of the string is based upon the hash operation that is applied on the aforesaid combination.

The distributed file system communicates the hash to the document sharing module. Optionally, the document sharing module is configured to communicate the hash of the document to the server arrangement.

Moreover, optionally, the document sharing module is configured to store the hash of the document on a blockchain platform, wherein the blockchain platform associates a timestamp with the hash of the document. Specifically, the blockchain platform relates to a distributed ledger arrangement that is configured to store a list of records. More specifically, in the blockchain platform, each block stores a cryptographic hash of a previous block, new information stored in the block and a timestamp associated with the block. Pursuant to embodiments of the present disclosure, the new information stored in the block comprises the hash of the document.

Furthermore, the blockchain platform is managed by a peer-to-peer network collectively adhering to a protocol for inter-node communication and validating new blocks in a blockchain. Moreover, once a block is stored in the blockchain (namely, the distributed ledger arrangement), the block cannot be altered. Thus, storing the hash of the document in the blockchain platform provides an immutable proof of publishing of the encrypted document with its associated timestamp.

Optionally, the server arrangement is configured to communicate the hash of the document to the second client device, for example, upon receipt or successful validation of the request for accessing the document. This enables the second client device to retrieve the encrypted document from the distributed file system.

Moreover, optionally, the document sharing module is configured to communicate to the second client device a key to be used to decrypt the encrypted document, upon successful validation of the request for accessing the document. This enables the second client device to decrypt the encrypted document using the key.

Furthermore, in some implementations, the second client device is configured to make a payment transaction for purchasing the document using the aforementioned blockchain platform.

Optionally, an appropriation module of the server arrangement is configured to prevent receipt of more than one copy of the document. In other words, the server arrangement employs the appropriation module to identify a facsimile of the document, wherein the facsimile of the document may or may not be submitted intentionally by the first client device. Specifically, upon the upload of a new document, the appropriation module identifies one or more value features of the new document, a summarized view of the new document, and a metainformation pertaining to the new document. Furthermore, the appropriation module compares the aforesaid information pertaining to the new document with the information pertaining to each of the plurality of documents already stored on the system. Subsequently, the appropriation module prevents the receipt of more than one copy (such as, a duplicate copy) of the document.

Optionally, the appropriation module is configured to identify equivalent documents based on the one or more value features of the document. In other words, the appropriation module identifies the equivalent documents (such as, a duplicate copy, an identical copy or an analogous copy) by comparing the one or more value features of the document against the value features of each of the plurality of documents stored in the server arrangement. Consequently, the appropriation module prevents a user of the first client device from providing the same document to the server arrangement more than once. Moreover, the appropriation module identifies any felonious action against the document such as theft, plagiarism, infringement and so forth.

For illustration purposes only, there will now be considered an example network environment, wherein the secure document management system can be implemented pursuant to embodiments of the present disclosure. One such network environment has been illustrated in conjunction with FIG. 1 as explained in more detail below.

The network environment includes a first client device and a second client device, a server arrangement of the system, a database arrangement associated with the server arrangement, and one or more data communication networks. The server arrangement, comprising one or more processors, is communicably coupled via the one or more data communication networks with the first client device and the second client device. Optionally, the network environment also includes a plurality of database servers communicably coupled via the one or more data communication networks with the one or more processors of the server arrangement.

It will be appreciated that it is not necessary for the one or more processors of the server arrangement to be coupled in communication with all the client devices simultaneously at all times.

The one or more data communication networks can be a collection of individual networks, interconnected with each other and functioning as a single large network. Such individual networks may be wired, wireless, or a combination thereof. Examples of such individual networks include, but are not limited to, Local Area Networks (LANs), Wide Area Networks (WANs), Metropolitan Area Networks (MANs), Wireless LANs (WLANs), Wireless WANs (WWANs), Wireless MANs (WMANs), the Internet, second generation (2G) telecommunication networks, third generation (3G) telecommunication networks, fourth generation (4G) telecommunication networks, fifth generation (5G) telecommunication networks and Worldwide Interoperability for Microwave Access (WiMAX) networks.

Examples of the first and second client devices include, but are not limited to, mobile phones, smart telephones, Mobile Internet Devices (MIDs), tablet computers, Ultra-Mobile Personal Computers (UMPCs), phablet computers, Personal Digital Assistants (PDAs), web pads, Personal Computers (PCs), handheld PCs, laptop computers, desktop computers, large-sized touch screens with embedded PCs, a server, and Network-Attached Storage (NAS) devices.

The one or more processors of the server arrangement are configured to execute machine readable instructions that cause the server arrangement to perform operations, for example, as illustrated with respect to the aforementioned first aspect.

The present description also relates to the method as described above. The various embodiments and variants disclosed above apply mutatis mutandis to the method.

Optionally, the method comprises implementing the extraction module either on the server arrangement or on the first client device, based on a preference of a user of the first client device.

Optionally, the method comprises converting a data format of the document into a predefined data format prior to extracting the one or more value features from the document, using the extraction module.

Optionally, the document is related to a current research work of one or more authors, and wherein the one or more value features of the document comprise information elements indicative of entities and semantic inter-relationships between the entities specific to the current research work.

Optionally, the method comprises using the scoring module to:

-   -   compare the entities and the semantic inter-relationships         specific to the current research work with entities and semantic         inter-relationships related to a technical field of the current         research work;     -   compare the entities and the semantic inter-relationships         specific to the current research work with entities and semantic         inter-relationships specific to a previous research work of the         one or more authors; and     -   determine the importance score based upon said comparisons.         Optionally, the method comprises using the scoring module to:     -   generate a current-work graph representing the entities and the         semantic inter-relationships specific to the current research         work;     -   generate a knowledge graph representing the entities and the         semantic inter-relationships related to the technical field of         the current research work;     -   generate a previous-work graph representing the entities and the         semantic inter-relationships specific to the previous research         work; and     -   perform said comparisons using the current-work graph, the         previous-work graph and the knowledge graph.

Optionally, the method further comprises storing the document on a temporary basis.

Optionally, the method comprises mapping a given concept to unique identifiers of a plurality of documents in which the given concept is identified, using the persistence module.

Optionally, the summarized view comprises a description of the document, bibliographical information pertaining to the document extracted based on the metainformation, a list of tags associated with the document, and the importance score of the document.

More optionally, the list of tags associated with the document comprises at least one of the one or more concepts associated with the document, wherein the at least one of the one or more concepts is selected based on a frequency of occurrence of the at least one of the one or more concepts in the document.

Optionally, the method further comprises displaying a list of summarized views of one or more documents whose unique identifiers are mapped to the at least one of the one or more concepts of the document, using a recommendation module of the server arrangement.

Optionally, the method further comprises using a document sharing module to:

-   -   encrypt the document using a key of the first client device; and     -   store the encrypted document in a distributed file system,         wherein the distributed file system is operable to generate a         hash that uniquely identifies the document.

More optionally, the method further comprises storing the hash of the document on a blockchain platform, wherein the blockchain platform associates a timestamp with the hash of the document.

Optionally, the method further comprises preventing receipt of more than one copy of the document, using an appropriation module of the server arrangement.

Optionally, the method comprises identifying equivalent documents based on the one or more value features of the document, using the appropriation module of the server arrangement.

DETAILED DESCRIPTION OF THE DRAWINGS

Referring now to the drawings, particularly by their reference numbers, FIGS. 1 and 2 are schematic illustrations of network environments, wherein a secure document management system for executing a document access transaction is implemented, pursuant to different embodiment of the present disclosure.

As shown in FIG. 1, the network environment 100 comprises a server arrangement 102 including one or more processors, a first client device 104, and a second client device 106. The server arrangement 102 is communicably coupled via one or more data communication networks (depicted as a data communication network 108) with the first client device 104 and the second client device 106.

The server arrangement 102 comprises a scoring module 110, a persistence module 112 and a validation module 114. As shown, the network environment 100 comprises an extraction module 116, implemented on the first client device 104. The extraction module 116 is communicably coupled to an ontological databank 118.

As shown in FIG. 2, the network environment 200 comprises a server arrangement 202 including one or more processors, a first client device 204, and a second client device 206. The server arrangement 202 is communicably coupled via one or more data communication networks (depicted as a data communication network 208) with the first client device 204 and the second client device 206. As shown, the network environment 200 comprises an extraction module 210, implemented on server arrangement 202, for receiving a document. The server arrangement 202 comprises a scoring module 212, a persistence module 214 and a validation module 216. The extraction module 210 is communicably coupled to an ontological databank 218.

FIGS. 1 and 2 are merely examples, which should not unduly limit the scope of the claims herein. It is to be understood that the specific designation for the network environments 100 and 200 are provided as an example and is not to be construed as limiting the network environments 100 and 200 to specific numbers, types, or arrangements of server arrangements, client devices, data communication networks and ontological databanks. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

FIG. 3 is a schematic illustration of a high-level architecture of a network environment 300 in which a system for executing a document access transaction is implemented, pursuant to a specific embodiment of the present disclosure.

The network environment 300 comprises a server arrangement 302 including one or more processors, a first client device 304 and a second client device 306. The server arrangement 302 is communicably coupled via one or more data communication networks (not shown) with the first client device 304 and the second client device 306.

With reference to FIG. 3, the network environment 300 comprises a distributed file system 308 and a blockchain platform 310.

The server arrangement 302 or the first client device 304 is configured to implement an extraction module (not shown) to extract value features from a document and metainformation pertaining to the document. The server arrangement 302 is configured to perform various operations, for example, as described earlier.

The first client device 304 is configured to encrypt the document and store the encrypted document in the distributed file system 308. The distributed file system 308 is operable to generate a hash that uniquely identifies the document and communicate the hash to the server arrangement 302.

The server arrangement 302 is configured to store the hash of the document on the blockchain platform 310, wherein the blockchain platform 310 associates a timestamp with the hash of the document.

The server arrangement 302 is configured to communicate the hash of the document to the second client device 306, for example, upon receipt of a request for accessing the document from the second client device 306, or upon successful validation of the request. This enables the second client device 306 to retrieve the encrypted document from the distributed file system 308.

The first client device 304 is configured to communicate to the second client device 306 a key to be used to decrypt the encrypted document, upon successful validation of the request for accessing the document. This enables the second client device 306 to decrypt the encrypted document using the key.

In some implementations, the second client device 306 makes a payment transaction for purchasing the document using the blockchain platform 310.

FIG. 3 is merely an example, which should not unduly limit the scope of the claims herein. It is to be understood that the specific designation for the network environment 300 is provided as an example and is not to be construed as limiting the network environment 300 to specific numbers, types, or arrangements of server arrangements, client devices, distributed file systems and blockchain platforms. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

Referring to FIGS. 4A and 4B, illustrated is a flow chart depicting steps of a method for managing documents in a secure manner, in accordance with an embodiment of the present disclosure. The method is depicted as a collection of steps in a logical flow diagram, which represents a sequence of steps that can be implemented in hardware, software, or a combination thereof, for example as aforementioned.

The method is implemented via a system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device

At a step 402, an extraction module is triggered to receive, from the first client device, a document and metainformation pertaining to the document.

At a step 404, the document is processed, via the extraction module, to extract one or more value features from the document based on an identification of one or more concepts of the document that are identified as associated with concepts stored in an ontological databank, the ontological databank being communicably coupled to the extraction module.

At a step 406, an importance score of the document is determined, using a scoring module of the server arrangement, based on the one or more value features and the metainformation pertaining to the document.

At a step 408, a summarized view of the document is constructed based on the one or more value features, the metainformation, the one or more concepts and the importance score.

At a step 410, a persistence module of the server arrangement is initialized to generate a unique identifier for the document and associate the unique identifier with the summarized view and with the one or more concepts of the document.

At a step 412, a search query is received from the second client device and processed to identify at least one concept pertaining to the search query.

At a step 414, the summarized view of the document based on the unique identifier of the document is retrieved when the at least one concept pertaining to the search query matches at least one of the one or more concepts of the document.

At a step 416, the summarized view of the document is displayed on a user interface of the second client device.

At a step 418, a request, received from the second client device, is validated for accessing the document using a validation module of the server arrangement, wherein the validation module is configured to cause the first client device to allow the second client device to access the document, when the request is validated successfully.

The steps 402 to 418 are only illustrative and other alternatives can also be provided where one or more steps are added, one or more steps are removed, or one or more steps are provided in a different sequence without departing from the scope of the claims herein.

FIGS. 5A and 5B are example views of a graphical user interface that are presented to a first user of a first client device, in accordance with an embodiment of the present disclosure. The graphical user interface allows the first user to submit a document and metainformation pertaining to the document.

With reference to FIG. 5A, a first example view includes text boxes and/or drop-down menus that allow the user to enter details and/or select a suitable option.

With reference to FIG. 5B, a second example view allows the user of the first client device to select one or more documents for submission.

FIGS. 5A and 5B are merely examples, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure. For example, another example view of the graphical user interface can show and allow the user to edit the information provided by the user.

FIGS. 6A and 6B are example views of a graphical user interface that are presented to a second user of a second client device, in accordance with an embodiment of the present disclosure. The graphical user interface allows the user of the second client device to input a search query and access the document.

With reference to FIG. 6A, a first example view includes input field for the search query. Subsequent to an input of the search query from the user, a list of documents related to the search query is shown.

With reference to FIG. 6B, a second example view illustrates a summarized view of a document, for example, based upon a user's selection from the list of documents.

FIGS. 6A and 6B are merely examples, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure. For example, another example view of the graphical user interface can allow user to access the document.

Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as “including”, “comprising”, “incorporating”, “have”, “is” used to describe and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural. 

What is claimed is:
 1. A secure document management system, the system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device, wherein the server arrangement is configured to: trigger an extraction module to obtain, from the first client device, a document and metainformation pertaining to the document; process the document via the extraction module, wherein the extraction module is configured to extract one or more value features from the document based on an identification of one or more concepts of the document that are identified as associated with concepts stored in an ontological databank, the ontological databank being communicably coupled with the extraction module; determine, using a scoring module of the server arrangement, an importance score of the document, wherein the scoring module is configured to determine the importance score based on the one or more value features and the metainformation pertaining to the document; construct a summarized view of the document based on the one or more value features, the metainformation, the one or more concepts and the importance score; initialize a persistence module of the server arrangement to generate a unique identifier for the document and associate the unique identifier with the summarized view and with the one or more concepts of the document; receive, from the second client device, a search query and process the search query to identify at least one concept pertaining to the search query; retrieve the summarized view of the document based on the unique identifier of the document, when the at least one concept pertaining to the search query matches at least one of the one or more concepts of the document; display, on a user interface of the second client device, the summarized view of the document; and validate a request, received from the second client device for accessing the document, using a validation module of the server arrangement, wherein the validation module is configured to cause the first client device to allow the second client device to access the document, when the request is validated successfully.
 2. The system of claim 1, wherein the extraction module is implemented either on the server arrangement or on the first client device, based on a preference of a user of the first client device.
 3. The system of claim 1, wherein the extraction module is configured to convert a data format of the document into a predefined data format prior to extracting the one or more value features from the document.
 4. The system of claim 1, wherein the document is related to a current research work of one or more authors, and wherein the one or more value features of the document comprise information elements indicative of entities and semantic inter-relationships between the entities specific to the current research work.
 5. The system of claim 4, wherein the scoring module is configured to: compare the entities and the semantic inter-relationships specific to the current research work with entities and semantic inter-relationships related to a technical field of the current research work; compare the entities and the semantic inter-relationships specific to the current research work with entities and semantic inter-relationships specific to a previous research work of the one or more authors; and determine the importance score based upon said comparisons.
 6. The system of claim 5, wherein the scoring module is configured to: generate a current-work graph representing the entities and the semantic inter-relationships specific to the current research work; generate a knowledge graph representing the entities and the semantic inter-relationships related to the technical field of the current research work; generate a previous-work graph representing the entities and the semantic inter-relationships specific to the previous research work; and perform said comparisons using the current-work graph, the previous-work graph and the knowledge graph.
 7. The system of claim 1, wherein the extraction module is further configured to store the document on a temporary basis.
 8. The system of claim 1, wherein the persistence module is configured to map a given concept to unique identifiers of a plurality of documents in which the given concept is identified.
 9. The system of claim 1, wherein the summarized view comprises a description of the document, bibliographical information pertaining to the document extracted based on the metainformation, a list of tags associated with the document, and the importance score of the document.
 10. The system of claim 9, wherein the list of tags associated with the document comprises at least one of the one or more concepts associated with the document, wherein the at least one of the one or more concepts is selected based on a frequency of occurrence of the at least one of the one or more concepts in the document.
 11. The system of claim 1, wherein a recommendation module of the server arrangement is configured to display a list of summarized views of one or more documents whose unique identifiers are mapped to the at least one of the one or more concepts of the document.
 12. The system of claim 1, wherein a document sharing module is configured to: encrypt the document using a key of the first client device; and store the encrypted document in a distributed file system, wherein the distributed file system is operable to generate a hash that uniquely identifies the document.
 13. The system of claim 12, wherein the document sharing module is configured to store the hash of the document on a blockchain platform, wherein the blockchain platform associates a timestamp with the hash of the document.
 14. The system of claim 1, wherein an appropriation module of the server arrangement is configured to prevent receipt of more than one copy of the document.
 15. The system of claim 14, wherein the appropriation module is configured to identify equivalent documents based on the one or more value features of the document.
 16. A method of managing documents in a secure manner, wherein the method is implemented via a system comprising a server arrangement including one or more processors, the server arrangement being communicably coupled via one or more data communication networks with a first client device and a second client device, the method comprising: triggering an extraction module to obtain, from the first client device, a document and metainformation pertaining to the document; processing the document, via the extraction module, to extract one or more value features from the document based on an identification of one or more concepts of the document that are identified as associated with concepts stored in an ontological databank, the ontological databank being communicably coupled with the extraction module; determining, using a scoring module of the server arrangement, an importance score of the document based on the one or more value features and the metainformation pertaining to the document; constructing a summarized view of the document based on the one or more value features, the metainformation, the one or more concepts and the importance score; initializing a persistence module of the server arrangement to generate a unique identifier for the document and associate the unique identifier with the summarized view and with the one or more concepts of the document; receiving, from the second client device, a search query and processing the search query to identify at least one concept pertaining to the search query; retrieving the summarized view of the document based on the unique identifier of the document, when the at least one concept pertaining to the search query matches at least one of the one or more concepts of the document; displaying, on a user interface of the second client device, the summarized view of the document; and validating a request, received from the second client device for accessing the document, using a validation module of the server arrangement, wherein the validation module is configured to cause the first client device to allow the second client device to access the document, when the request is validated successfully.
 17. The method of claim 16, further comprising implementing the extraction module either on the server arrangement or on the first client device, based on a preference of a user of the first client device.
 18. The method of claim 16, further comprising converting a data format of the document into a predefined data format prior to extracting the one or more value features from the document, using the extraction module.
 19. The method of claim 16, wherein the document is related to a current research work of one or more authors, and wherein the one or more value features of the document comprise information elements indicative of entities and semantic inter-relationships between the entities specific to the current research work.
 20. The method of claim 19, further comprising using the scoring module to: compare the entities and the semantic inter-relationships specific to the current research work with entities and semantic inter-relationships related to a technical field of the current research work; compare the entities and the semantic inter-relationships specific to the current research work with entities and semantic inter-relationships specific to a previous research work of the one or more authors; and determine the importance score based upon said comparisons.
 21. The method of claim 20, further comprising using the scoring module to: generate a current-work graph representing the entities and the semantic inter-relationships specific to the current research work; generate a knowledge graph representing the entities and the semantic inter-relationships related to the technical field of the current research work; generate a previous-work graph representing the entities and the semantic inter-relationships specific to the previous research work; and perform said comparisons using the current-work graph, the previous-work graph and the knowledge graph.
 22. The method of claim 16, further comprising storing the document on a temporary basis.
 23. The method of claim 16, further comprising mapping a given concept to unique identifiers of a plurality of documents in which the given concept is identified, using the persistence module.
 24. The method of claim 16, wherein the summarized view comprises a description of the document, bibliographical information pertaining to the document extracted based on the metainformation, a list of tags associated with the document, and the importance score of the document.
 25. The method of claim 24, wherein the list of tags associated with the document comprises at least one of the one or more concepts associated with the document, wherein the at least one of the one or more concepts is selected based on a frequency of occurrence of the at least one of the one or more concepts in the document.
 26. The method of claim 16, further comprising displaying a list of summarized views of one or more documents whose unique identifiers are mapped to the at least one of the one or more concepts of the document, using a recommendation module of the server arrangement.
 27. The method of claim 16, further comprising using a document sharing module to: encrypt the document using a key of the first client device; and store the encrypted document in a distributed file system, wherein the distributed file system is operable to generate a hash that uniquely identifies the document.
 28. The method of claim 27, further comprising storing the hash of the document on a blockchain platform, wherein the blockchain platform associates a timestamp with the hash of the document.
 29. The method of claim 16, further comprising preventing receipt of more than one copy of the document, using an appropriation module of the server arrangement.
 30. The system of claim 29, further comprising identifying equivalent documents based on the one or more value features of the document, using the appropriation module of the server arrangement. 